Files
AgapHost/openai/cognee-llm/README.md
alvis b27d31b3ca openai: compose healthchecks + dependency ordering, registries, LiteLLM routing
docker-compose.yml gains healthchecks and depends_on/condition chains for the
litellm/langfuse/postgres tier so dependants wait for a genuinely ready
service instead of a started container. Also plumbs AGAP_MCP_TOKEN into the
adolf and adolf-llm containers, sourced from openai/.env (gitignored), for the
kb#180 bearer auth on the agap MCP server; shared-mcp.json consumes it via
bearerTokenEnvVar so the Kimi backbone authenticates too.

agent-registry.yaml / agent_registry.py: the version-controlled source of
truth for agent identities and trust classes -- the same ids the agap-mcp
token map resolves to (`adolf`, `claude-coder`; note `claude-code-cli` is the
runtime entry, not an agent identity).

model-registry.yaml, litellm-config.yaml, auto-router-routes.json and
provision_litellm_keys.py: model tiering, virtual-key provisioning and
auto-router routes. tei-reranker/ is the local reranker service backing
Hindsight recall.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-07-30 04:41:31 +00:00

3.3 KiB

cognee-llm (:8011)

⚠️ SUPERSEDED — Adolf's memory is migrating Cognee → Hindsight (2026-07-13). Hindsight runs its LLM on LiteLLM :4000 / Ollama, so this bespoke Kimi-CLI wrapper is being retired, not ported (SPIKE gate 5 already concluded the extraction workload shouldn't sit on the Kimi seat). This service is decommissioned in migration task H4. Plan: agap_git/adolf/HINDSIGHT-MIGRATION.md. The doc below describes the outgoing Cognee stack, kept until H4 lands.

OpenAI-compatible wrapper around the Kimi Code CLI (@moonshot-ai/kimi-code, home /root/.kimi-code), built for Cognee's batch/structured LLM calls. Opposite policy to kimi-agent:

  • Stateless one-shot — fresh temp dir under /workspace/<uuid> per request, kimi -p <prompt> --output-format stream-json, no -r/-S resume, dir removed after every call (success or failure).
  • Non-streaming — always returns a full chat.completion body, even if the caller sets stream: true.
  • No media, no MCP — text-only prompt built from messages; no image persistence, no .mcp.json.
  • Structured/low-temperature intent via prompt, not a sampling param — the CLI has no raw temperature knob (it's an agent loop, not a completions API), so determinism/JSON-only output is enforced with an instruction preamble prepended to the caller's system prompt.
  • Bounded concurrencyMAX_CONCURRENCY = 3 in server.js, queued beyond that.

Endpoints: GET /v1/models (model id cognee-llm), POST /v1/chat/completions.

Own disposable in-container /workspace (no host bind mount — nothing here is meant to survive a request, let alone a container restart) + own cognee-llm-home volume (/root/.kimi-code), same Kimi subscription as kimi-agent/adolf-llm, separate volume so each wrapper's CLI state stays isolated.

This IS Cognee's LLM backbone

By design, Cognee's LLM runs on the flat Kimi subscription through this wrapper — the whole reason it exists — mirroring how adolf-llm backs the assistant. P4 wires cognee's LLM_ENDPOINThttp://cognee-llm:8011, LLM_MODELopenai/cognee-llm.

Accepted tradeoff (SPIKE-FINDINGS gate 5). The CLI's JSON output is clean/schema-conformant, but it's slower than a raw API: ~5s fixed per-invocation floor + ~22-24s for a realistic structured-extraction call, and every call is agentic. Cognify issues one call per chunk/entity-extraction step, so large batches serialize into minutes. To protect the single-seat subscription, MAX_CONCURRENCY = 3 bounds concurrent spawns.

Documented fallback (not the default): if cognify throughput ever becomes a real problem, route cognee's LLM to a LiteLLM model instead (ARCHITECTURE.md §3.3) — see the commented block in cognee/cognee.env. Embeddings already run on LiteLLM's nomic-embed regardless (embeddings can't go through the agentic CLI).

Smoke test

cd /home/alvis/agap_git/openai
docker build -t cognee-llm:local ./cognee-llm
docker run --rm -d --name cognee-llm-smoke -p 18011:8011 cognee-llm:local
curl -s http://localhost:18011/v1/models
docker rm -f cognee-llm-smoke

A full /v1/chat/completions round-trip needs a kimi login-authed /root/.kimi-code volume (shared Kimi subscription) — not present in a bare smoke container, so that step is deferred to integration/P4 wiring.